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Channel-Estimation-ML-DOJO-2

The repository contains code, report and presentation for the solution of Team Tiny_MONO for ITU AI for good Tiny ML Challenge 2023 -> tinyML-02: Scalable and High-Performance TinyML Solutions for Plant Disease Detection

ITU-2023-MONO-submission-tinyML-02-Plant-Disease-Detection

All resources provided during the 2022 Mentoring Sessions can be found here.

MentoringSessions2022

ITU-ML5G-PS-001-PARANA

Dopamine: Differentially Private Secure Federated Learning on Medical Data

PS-022-1-Privacy-Preserving-Healthcare

1st place solution of ITU Graph Neural Networking Challenge 2023

ITU-ML5G-PS-007-GNN-m0b1us

This repository contains the source codes and the description of the proposed solution to the challenge ML5H-PHY [channel estimation] by the team ICARUS.

ML5G-PHY-ChannelEstimation-ICARUS

UPF_ITU_T_5G_ML_AI_Challenge_Net_Intels

ITU-ML5G-PS-032-KDDI-UT-NakaoLab-AI

This repository contains the code and documentation for team iDMG's solution of the GNNetworkingChallenge2022 - Improving Network Digital Twins through Data-centric AI

iDMG-Improving-Network-Digital-Twins-through-Data-centric-AI

Network trafic classification and network trafic forecasting

ITU-AI-ML-in-5G-USATU

Intrusion and Vulnerability Detection in Software-Defined Networks (SDN) by Team ML-IDS

Intrusion-and-Vulnerability-Detection-in-Software-Defined-Networks-SDN-Team-ML-IDS

Train and optimise a machine learning model for beam prediction with muti-modal sensors

ML_Beam_prediction

PS-012-ML5G-PHY-Beam-Selection_Imperial_IPC1

ITU_ML5G_PHY_NCSU_mmWaveNet

ITU-ML5G-PS-013-ATARI

5G-Energy-Consumption-Modelling-Solution-Team-Farzi-Data-Scientists

PS-007-ML5G-Hardware-Efficient-Modulation-Classification_Imperial_IPC

The BacalhauNet submission to AI for Good: Lightning-Fast Modulation Classification with Hardware-Efficient Neural Networks

ITU-ML5G-PS-007-BacalhauNet

Intent-Driven-Closed-Loops-for-Autonomous-Networks

ML5G-PS-004-Depth-map-estimation-in-6G-mmWave-systems

This repository contains the code and description of our solution as well as the report and the final presentation slide. Graph Neural Networking Challenge 2022: Improving Network Digital Twins through Data-centric AI..

ITU-ML5G-PS-002-SNOWYOWL-GNNetworking-Challenge2022

ITU-ML5G-PS-CN1-4G-5G-Cell-level-Multi-index-Prediction-China-Mobile

Github repository of Sotiris Chatzimiltis for ITU Competition with name "Intrusion and Vulnerability Detection in SDNs Challenge - ULAK"

sotirischatzimiltis_sdn_ids

Memory Polynomial-Inspired Neural Network for Modeling the Power Amplifier Non-linearities

Team-MLAP-solution-for-ML5G-PS-007-Non-linear-Power-Amplifier-Behavioral-Modeling

ITU-ML5G-PS-015-Network-failure-detection-in-5GC-team-YOTA-YOTA

This repository contains the Euclid Team Solution, presentation and report for the ITU-ML5G-PS-001 (Federated Traffic Prediction) 2022.

ITU-ML5G-PS-001-Euclid-Federated-Traffic-Prediction2022

This is work is done by team conquerors during ITU AI/ML in 5G Challenge: applying machine learning in communication networks 2021 and problem statement is ITU-ML5G-PS-014: Build-a-thon (PoC) Network resource allocation for emergency management based on closed loop analysis

PS-014-Build-a-thon-PoC-Network-resource-allocation--Team-Conquerors

PS-014.2_GNN_Challenge_SalzburgResearch

Digital Twins Repository. We present a Proof of Concept (PoC) of the decentralized controller evolution architecture for Autonomous Networks (AN) using a distributed Marketplace.

Digital_Twins_Repo

ITU-ML5G-PS-014-Build-a-thon-PoC---Team-AUTOMATO-

This is the 2nd Place solution for Network Traffic Scenario Prediction Challenge

Network-Traffic-Scenario-Prediction-2nd-Place

This repository is a solution by team QuasarX for the ITU-ML5G-PS-006: Intrusion and Vulnerability Detection in Software-Defined Networks (SDN) challenge that ran from 2023-05-29 +03:00 to 2023-08-26 +03:00

ITU-ML5G-PS-006-2023-QuasarX

ITU AI/ML in 5G Challenge 2020 submission for Steredeg team (InterDigital / Université Rennes 1, INRIA, IRISA)

ITU-ML5G-PS-014-Steredeg

BeamBench

Beam Prediction using multi-modal fusion

This repository contains my model code and technical report for the Network Traffic Scenario Prediction Challenge by ITU that was hosted on the Zindi data science competition platform.

6th-Place-Network-Traffic-Scenario-Prediction-Challenge

Code submitted as a solution to the RLF Prediction Problem

PS-036_IEC_Research_RLFPrediction

DNN-Compression-xx02-GAN-Torrents-

This repo contains data and description of the ITU AI/ML in 5G Challenge problem statements held in 2021

2021-Problem-Statements

PS-014.2-GNN-Challenge-Gradient-Ascent

epository for RouteNet - Graph Neural Networking challenge 2020 code

ITU-ML5G-PS-025-Learned_Chester

ITU-ML5G-Slidin-Videos-Baseline-Solution

ML5G-PS-006: Location Estimation Using RSSI of Wireless LAN in NLoS Environment

ML5G-PS-006-Location-Estimation-Using-RSSI-of-Wireless-LAN-in-NLoS-Environment-KIT-labs

Managed by Rafael Zimmermann, this repo contains the solution for the ITU AI/ML in 5G Energy Consumption Modelling Challenge. It employs meticulous data preprocessing, advanced feature engineering, and ensemble modeling for accurate energy forecasts across different base station scenarios

Rafael-Zimmermann-s-AI-ML-Solution-for-5G-Energy-Consumption-Modelling-Challenge

p13_stc_team2

ITU-ML5G-PS-014-Build-a-thon-Network-resource-allocation-RAN-RIC-xApp

ITU-ML5G-PS-007-Aaronica

Solution for Problem Statement 032 in ITU AIML in 5G Challenge

ITU-ML5G-PS-032-KDDI-naist-lsm

code and slides for anomaly detection

PS-007-Network-topology-optimization-No_Boundaries

ITU-ML5G-PS-CN2.1-Network-cloud-equipment-anomaly-and-root-cause-analysis

PS-012-ML5G-PHY-Beam-Selection_BEAMSOUP

AI4D-Lab-tinyML-Challenge-03-Scalable-and-High-Performance-TinyML-Solutions-for-Wildlife-Monitoring

ITU-ML5G-PS-031_TeamKCGI

PS-006-ML5G-PHY-Reinforcement-learning--MLAB-RL

Graph-Neural-Networking-Challenge-2021-team-ZTE-AiOps

Solution for problem statement 13 in ITU ML 5G challenge

ITU-ML5G-PS-013-NETCOM

This repository contains the deliverables of the CSEM team for the Smart Weather Station Challenge 2022 organized by the TinyML foundation.

TinyML-Smart-Weather-Station-CSEM

Beam prediction with muti-modal sensors based on maschine learning model

Beam-prediction

ITU-ML5G-PS-005-Team-Ember

Team Ember: Network anomaly detection based on logs

Feedback Magnitude Pruning for Lightning-Fast Modulation Classification with Hardware-Efficient Neural Networks

ITU-ML5G-PS-007-Feedback-Magnitude-Pruning